Communication Systems and Applications

Digital predistortion is applied to account for all significant
hardware impairments in a regeneration architecture full-duplex
transceiver. Compared to a conventional regeneration
architecture, where non-linearities are simply reconstructed
for cancellation, by predistorting we avoid these components
to achieve an improvement in both self-interference suppression
and signal quality. A new set of predistortion basis functions
is proposed for the cascade of baseband non-linearities,

In this paper, we propose a scheme for distributed source coding, using low-density parity-check (LDPC) codes to compress close to the Slepian-Wolf limit for correlated binary sources. First, we develop a conventional Belief Propagation (BP) algorithm LDPC decoder which takes the syndrome information into account. Subsequently, modelling the correlation between the sources as a binary symmetric channel (BSC), we replace the received probabilities in the conventional channel with the cross over probability.

Complex sequences with constant magnitude in the time domain and good aperiodic autocorrelation properties are of fundamental interest due to its applications. Their design typically involves the minimization of a nonlinear function that strives to make equal to zero the correlation coefficients in a region of interest. In this letter, the design of unimodular sequences whose aperiodic autocorrelation and aperiodic complementary autocorrelation vanish for a given set of lags is proposed.

Complex sequences with constant magnitude in the time domain and good aperiodic autocorrelation properties are of fundamental interest due to its applications. Their design typically involves the minimization of a nonlinear function that strives to make equal to zero the correlation coefficients in a region of interest. In this letter, the design of unimodular sequences whose aperiodic autocorrelation and aperiodic complementary autocorrelation vanish for a given set of lags is proposed.

Complex sequences with constant magnitude in the time domain and good aperiodic autocorrelation properties are of fundamental interest due to its applications. Their design typically involves the minimization of a nonlinear function that strives to make equal to zero the correlation coefficients in a region of interest. In this letter, the design of unimodular sequences whose aperiodic autocorrelation and aperiodic complementary autocorrelation vanish for a given set of lags is proposed.

Cellular backhaul networks usually consist of commercial microwave links, known to be sensitive to weather conditions. The management network systems usually provide records of measurements of the transmitted and the received signals levels from the different microwave links for monitoring and analyzing the network performance. Many of them log only the minimum and the maximum levels of the transmitted and the received signals in pre-set intervals (usually 15-minute). Moreover, only quantized version of these measurements are logged.

In this work, we propose a new symbol detection method in faster-than-Nyquist signaling for effective data transmission. Based on the frame theory, the symbol detection problem is described as under-determined linear equations on a finite alphabet. While the problem is itself NP (non-deterministic polynomial-time) hard, we propose convex relaxation using the sum-of-absolute-values optimization, which can be efficiently solved by proximal splitting. Simulation results are shown to illustrate the effectiveness of the proposed method compared to a recent ell-infinity-based method.

Optical wireless communications (OWC) in general
and resource allocation in OWC networks particularly have
gained lots of attention recently. In this work, we consider the
resource allocation problem of a visible light communication
downlink transmission system based on time division multiple
access with the objective of maximizing spectral efficiency (SE).
As for the operational conditions, we impose constraints on
the average optical intensity, the energy consumption and the

This paper proposes regularized version of Variable Step Size Normalized Least Mean Square algorithm (RVSSNLMS) for iterative channel estimation scheme in MC-IDMA system. The proposed scheme is based on the exploitation of the inherent sparsity in the OFDM channels.